Abstract A040: Intra-epithelia cell dynamics shape evolutionary dynamics and selection of therapy resistant clones in lung cancer
Authors: Xiao Fu, Ajay Bhargava, Sasha Bailey, Dhruva Biswas, Carlos Martinez Ruiz, Sunil Kumar, Paul French, Nicholas McGranahan, Charles Swanton, Paul A. Bates, Erik Sahai
Journal: Cancer Research (2022)

Abstract Lung cancer is a leading cause of cancer-related deaths. Despite enhanced characterization of genomic complexity and intra-tumor heterogeneity that underpin therapy failure, the mechanistic and predictive factors shaping and steering evolutionary dynamics remain less clear. In this study, we combined experimental, computational, and tumor molecular data analysis approach to investigate factors and rules governing evolutionary dynamics in lung cancer. A lineage tracing study in a BL/6 KRASG12D TP53mutant lung adenocarcinoma cell line model uncovers unexpected variation in the long-term fate of clones with no selective advantage or disadvantage, with clones arising near the edge of tumor colonies being favored to expand. An agent-based computational model of cell proliferation and cell-cell physical interaction, incorporating the experimentally driven assumption of compression-induced non-proliferation, recapitulated the growth patterns of tumor colonies and unequal expansion of clones. By further implementing cell random motility, the model predicts that enhanced motility destabilizes cell-cell cohesion and causes spatial clone intermixing with altered size distributions. Corroborating the observations in silico, experimental manipulations that increase the migratory capabilities of cancer cells relieve density-driven growth arrest and lead to clone intermixing in vitro. Furthermore, lung cancer cell lines with more migratory properties exhibit less propensity for suppression of proliferation. To relate findings in our models to tumor data and to infer the degree of clone intermixing in patients, we implemented a mutational process in the computational model and extracted features of variant allele frequency that enable to distinguish model runs with higher or lower degree of clone intermixing. Inference in lung adenocarcinomas in the TRACERx (TRAcking Cancer Evolution through therapy (Rx)) Lung study using these features, cross-referenced with RNA sequencing data in the same tumors, reveals notable correlation between mechanisms driving cell migration in our experimental models and inter-subclone mixing in clinical samples. Finally, modelling the competition between sensitive and mutagenesis-derived resistant clones under a virtual cytotoxic therapy predicts an accelerated selection of therapy resistant clones under conditions with enhanced cell motility. In summary, our integrated study demonstrates that intra-epithelia cell dynamics dictates the fates of clones both under neutral evolution and under selective pressures imposed by therapy. Citation Format: Xiao Fu, Ajay Bhargava, Sasha Bailey, Dhruva Biswas, Carlos Martinez Ruiz, Sunil Kumar, Paul French, Nicholas McGranahan, Charles Swanton, Paul A. Bates, Erik Sahai. Intra-epithelia cell dynamics shape evolutionary dynamics and selection of therapy resistant clones in lung cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr A040.